What you'll need 8+ years of experience in Car insurance pricing, actuarial science, decision science, risk analytics, or a closely related field A proven track record solving complex pricing, underwriting, segmentation, or risk-management problems with measurable business impact Strong analytical instincts - knowing how to find signal in data, make decisions under uncertainty, and separate elegant analysis from useful analysis Hands-on fluency with modern analytical tools, agentic AI capabilities, and code - including experience using generative AI, coding agents, or advanced automation to materially improve analytical workflows Solid understanding of Car insurance pricing fundamentals, including rating plans, loss costs, rate adequacy, segmentation, model validation, telematics and financial performance. Familiarity with predictive modeling methods such as GLMs, gradient boosting, random forests, clustering, and feature engineering Experience building or modernizing pricing platforms, rating engines, underwriting tools, or internal decision-support software Product-minded problem solving: the ability to turn a messy workflow, technical constraint, or business problem into a clear, prioritized path forward - with a track record of partnering with Product and Engineering teams to ship production-grade tools Strong communication skills - you can explain pricing decisions, tradeoffs, and model outputs clearly to executives, engineers, product teams, and regulators Comfort operating in a fast-moving environment where ownership matters, ambiguity is normal, and AI is part of how work gets done Experience leading pricing work across multiple geographies, products, or regulatory environments is a strong plus Formal actuarial credentials, such as Fellow or Associate of a recognized actuarial society, are a plus Bachelor's degree in Actuarial Science, Mathematics, Statistics, Computer Science, Economics, Engineering, or a related quantitative field Ready to wor
